Robust Decentralized Dynamic State Estimation Considering Instrumentation Chain Anomalies

A decentralized method for estimating the interior states of a synchronous machine using analogue measurements from instrument transformers (that is, current transformer and potential transformer) has been proposed in this paper. The method is robust to instrumentation chain anomalies, which have not been considered in the existing dynamic state estimation literature. The method works in a two-step manner, wherein a robust adaptive detection scheme removes instrument transformer anomalies, harmonics, noise, and DC components, and estimates the phasors of the analogue measurements, and subsequently uses these estimated phasors in the decentralized dynamic state estimation algorithm. Robust and adaptive version of square-root-cubature-Kalman-filter has been employed to enhance estimation accuracy irrespective of the type of noise distribution. The superiority of the algorithm over existing methods has been established in terms of numerical accuracy, computational efficacy, and robustness. IEEE 68 bus power system has been used to test the effectiveness of the developed strategy. Opal-RT based setup has also been used to implement the case studies in real-time.